1. Field of the Invention
This invention relates to an image processing system for recognizing shapes in images acquired by cameras or other means. In particular, the system enables deriving primitive shape elements of a shape in an image which may be combined to form a description of the shape. This description then may be used to index a library of known shapes.
2. Description of the Prior Art
One of the most difficult problems in image processing is image recognition. Image recognition seeks to process images acquired using cameras or other means in a manner which extracts information content from the image, for example, for optical character recognition, quality control, remote sensing, and a host of other applications. Many different approaches have been tried for automated image recognition.
One of the oldest approaches is statistical pattern recognition, which entails forming a vector from some number of measurements deemed to be relevant to the recognition task. The hyperspace position of this multidimensional vector then is compared with the positions of like-generated vectors for a large set of known shapes, and a statistical decision made based on which shape category is most likely. This approach is simple and can be made to work well in specialized domains. The primary disadvantage is that it is incomplete. There is no real theory for what the vector measurements should be.
Template matching is another approach to image recognition. In template matching, images of each of the shapes to be recognized are stored, and each compared with the unknown image shape to determine which is most similar. This approach is again simple and easy to use in some specialized applications, but can be very expensive both in storage and search time when the domain is expanded. A further limitation arises from the static nature of the stored templates. It is difficult to allow for some kinds of flexibility in the shape definitions without significantly reducing the overall acuity of the method.
A variation of the template approach that overcomes some of these weaknesses uses templates for more primitive shape components, rather than complete shapes. For example, templates for various kinds of corners and edges are employed to construct a description of a shape. This description then can be supplied to a statistical pattern recognition system or it can be used to build a structural description.
A third approach to image recognition attempts to build a description of the geometrical structure of a shape and then use that description as an index into a catalog of known shapes. This approach has the potential for handling extremely large data bases of known shapes efficiently because lookup does not require examining everything. Additionally, arbitrarily fine distinctions can be made as the search homes. To make it work, however, requires organizing the shape catalog so that items can be found reliably from their descriptions.